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Inside TensorFlow: TensorFlow Lite
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Take an inside look into the TensorFlow team’s own internal training sessions--technical deep dives into TensorFlow by the very people who are building it. On this episode of Inside TensorFlow, Software Engineer Jared Duke gives us a high level overview of TensorFlow Lite and how it lets you deploy machine learning models on mobile and IoT devices. Let us know what you think about this presentation in the comments below!
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Links:
0:37:31
Inside TensorFlow: TensorFlow Lite
0:37:32
Inside TensorFlow: New TF Lite Converter
0:06:04
Introducing TensorFlow Lite (Coding TensorFlow)
0:13:30
Optimize your TensorFlow Lite models | Session
0:54:30
Building with TensorFlow Lite for microcontrollers | Workshop
0:00:17
Machine Learning on Arduino with TensorFlow Lite Micro
0:06:06
TensorFlow Lite for Android (Coding TensorFlow)
0:01:52
TensorFlow Lite C++ ( Introduction)
0:12:04
On-device object detection: Train and deploy a custom TensorFlow Lite model
0:02:37
How to convert your ML model to TensorFlow Lite (TensorFlow Tip of the Week)
0:23:18
How to Train TensorFlow Lite Object Detection Models Using Google Colab | SSD MobileNet
0:45:54
TensorFlow Lite in Android with Google Play services
0:33:43
TensorFlow Lite: Solution for running ML on-device (TF World '19)
0:01:11
TensorFlow Lite for Microcontrollers
0:00:11
Tensorflow Lite Example
0:44:45
TensorFlow Lite (TF Dev Summit ‘19)
0:42:35
Inside TensorFlow: TF Model Optimization Toolkit (Quantization and Pruning)
0:34:28
AI Landmark Recognition With Tensorflow Lite and CameraX on Android
0:03:46
TensorFlow Lite, Experimental GPU Delegate (Coding TensorFlow)
0:59:21
TensorFlow Lite for Edge Devices - Tutorial
0:02:25
Easily deploy TF Lite models to the web | Demo
0:43:41
Inside TensorFlow: MLIR for TF developers
0:18:36
TinyML: Getting Started with TensorFlow Lite for Microcontrollers | Digi-Key Electronics
0:07:24
TensorFlow Lite for on-device ML (TensorFlow Meets)
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